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Theoretical and Applied Climatology

, Volume 99, Issue 3–4, pp 255–272 | Cite as

Climate version of the ETA regional forecast model

Evaluating the consistency between the ETA model and HadAM3P global model
  • I. A. Pisnichenko
  • T. A. Tarasova
Original Paper

Abstract

A new version of ETA WS (workstation) forecast model destined for long-term climate change simulation (ETA CCS) was designed. Numerous modifications and corrections have been made in the original code of the ETA WS forecast model. As a first step in the ETA CCS validation program, we have integrated the model over South America with a horizontal resolution of 40 km for the period 1960–1990. We forced it at its lateral boundaries by the outputs of HadAM3P, which provides a simulation of modern climate with a resolution of about 150 km. The climate ETA model was run on the supercomputer SX-6. Here, we present and compare the output fields of the ETA model and HadAM3P and analyze the geopotential, temperature, and wind fields of both models. For evaluating the similarities of the model outputs, we used a Fourier analysis of time series, the consistency index from linear regression coefficients, the time mean and space mean models’ arithmetic difference and root mean square difference. The results of the study demonstrate that there are no significant differences in behavior and spatial arrangement of large-scale structures of the two models. In addition, the regional model characteristics do not have major positive or negative trends during the integration in relation to the global model. Our analysis shows that the descriptions of large-scale climate structures by these two models are consistent. This means that the ETA CCS model can be used for downscaling HadAM3P output fields. Our proposed technique can be used to evaluate the consistency of any regional model and its driving global model.

Keywords

Regional Climate Model Geopotential Height Root Mean Square Difference Consistency Index South Atlantic Convergence Zone 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

I.A. Pisnichenko was supported by Global Opportunity Fund (GOF) from UK Foreign Commonwealth Office, T.A. Tarasova was sponsored by INPE/CPTEC as part of an international agreement with the NEC Corporation. The authors thank Hadley Center for presenting HadAM3P data. We also acknowledge Prof. R. Laprise for useful discussion during preparing manuscript.

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.Center of Weather and Climate Studies/National Institute of Space Research (CPTEC/INPE)Cachoeira PaulistaBrazil
  2. 2.Center of Earth System Science/National Institute of Space Research (CCST/INPE)Cachoeira PaulistaBrazil
  3. 3.Institute of Atmospheric PhysicsRussian Academy of SciencesMoscowRussia

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